1. Field of the Invention
The present invention is directed to the fields of data mining and query processing, and more specifically, for methods for analyzing behaviors of search engine users to detect associations between particular search strings and items.
2. Description of the Related Art
Many World Wide Web sites permit users to perform searches to identify a small number of interesting items among a much larger domain of items. As an example, several web index sites permit users to search for particular web sites among most of the known web sites. Similarly, many online merchants permit users to search an electronic catalog for particular products. In many cases, users perform searches in order to ultimately find a single item within an entire domain of items.
To perform a search, a user submits a search query, usually in the form of a string of characters with one or more terms. The query may also explicitly or implicitly identify a domain of items to search. For example, a user may submit a query to an online bookseller containing terms that the user believes are words in the title of a book. A query server program processes the query to identify, within the domain, items matching the terms of the query. The items identified by the query server program as matching the search query (and in some cases, as nearly matching the search query) are collectively referred to as the query result. This set of items may be ordered for display in various ways. For example, the list may be ordered based on the extent to which each identified item matches the terms of the query, based on the popularity levels of the responsive items, and/or other criteria.
To improve the relevance of the query results presented to users, some search engine systems monitor and analyze the search-related behaviors of users to detect and quantify associations between particular search strings and items. For example, in the context of a product catalog, if a relatively large percentage of the users who submit the search string “Apple” select an Apple iPod™ Shuffle from the corresponding search results pages, the search engine system may create an association between this search string and product. As another example, in the context of a search engine for searching the World Wide Web, if a relatively large percentage of those who search for “tax return” select the web site “www.irs.gov,” an association may be created between this search string and web site.
The detected string/item associations may be used to provide more relevant search results to users by increasing the rankings of the items most closely associated with a user's search string. For instance, in the example above with the search term “Apple,” when a user conducts a catalog search for “Apple,” the search engine may display the iPod Shuffle item at the top of the search results listing.
Unfortunately, existing methods sometimes fail to accurately detect and quantify behavior-based associations between search strings and items.